The workflow is presented on a case study from the North-Central Vandans region, situated in the South-West of the Vorarlberg Alps in the West of Austria. The Region of Interest (ROI) lies on the West mountainside of the Mädli, North of Voralpe Vilifrau. The ROI (250 x 190 m) was chosen at the upper treeline, which can be described as an abrupt diffuse krummholz treeline according to the classification of @baderGlobalFrameworkLinking2021, taking the young trees and occasional shrubs/krummholz below and around the treeline into account. Figure 3 describes the situation best.
Schematic depiction of the ATE. It clearly sets the ROI of this case study above the timberline and still around the treeline. Source: Barredo Cano et al. (2020)
In this project LIDAR data (without any metadata and also the date of acquisition) as well as RGB and IR (Infra-Red) Aerial Imagery from 2012 was used, all downloaded from the VoGIS website.
For the development of the workflow 4 test areas were defined inside
the ROI to first test the values of the different algorithms on test
area 1 and if needed also on the rest of the rest areas. Originally
masks for each 4 test areas were created in QGIS and based on them, the
Canopy Height Model (CHM) and the RGB and IR Aerial Imagery was cropped
to the size of the test area masks. When it became clear, that the
minimal computable raster size (on grounds of the restrictions of the
raster package in R) was a lot smaller than
the maximum size of the actual ROI originally decided, it was reduced.
The sizes of the CHM test areas were defined using the ‘Clip
raster by Extent’ tool, with the ‘use map
canvas’ setting in QGIS, to define 4, approximately 32 x
32 m test areas (Figure 4). Then the respective CHM
test areas were used as masks/extents to clip the respective RGB and IR
test areas in QGIS.